Email: dushyant_at_robots.ox.ac.uk

Dushyant’s Google Scholar Page

Dushyant Rao joined the Mobile Robotics Group in 2016 as a postdoctoral researcher, working on perception and planning for autonomous ground vehicles.

Research

Dushyant is currently pursuing the following research topics:

  • Multimodal object detection and classification from LIDAR and camera data
  • Adaptive representation learning for lifelong perception
  • Online semi-supervised learning and multi-task learning

Bio

Dushyant holds a BEng (Mechatronics – Space) and BSc (Nanoscience) from the University of Sydney, an MSc in Aerospace Engineering from the University of Illinois at Urbana-Champaign, and a PhD from the Australian Centre for Field Robotics at the University of Sydney. His PhD research was on multimodal deep learning for autonomous underwater vehicles from visual images and sonar data. In addition, his undergraduate and master’s theses were focused on motion planning for an underwater glider, and localisation & mapping for a micro-aerial vehicle, respectively.

In his spare time, Dushyant is an avid guitarist and loves to travel.

 

MRG Publications

2017

  • [PDF] J. Dequaire, P. Ondrúška, D. Rao, D. Wang, and I. Posner, “Deep tracking in the wild: End-to-end tracking using recurrent neural networks,” The International Journal of Robotics Research, 2017.
    [Bibtex]

    @article{DequaireIJJ2017,
    author = {Dequaire, Julie and Ondr{\'u}{\v{s}}ka, Peter and Rao, Dushyant and Wang, Dominic and Posner, Ingmar},
    title = {Deep tracking in the wild: End-to-end tracking using recurrent neural networks},
    year = {2017},
    eprint = {http://journals.sagepub.com/doi/abs/10.1177/0278364917710543},
    journal = {The International Journal of Robotics Research},
    publisher={SAGE Publications Sage UK: London, England},
    Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017_IJRR_Dequaire.pdf}
    }

  • [PDF] M. Engelcke, D. Rao, D. Zeng Wang, C. Hay Tong, and I. Posner, “Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2017.
    [Bibtex]

    @inproceedings{EngelckeICRA2017,
    author = {Engelcke, M. and Rao, D. and Zeng Wang, D. and Hay Tong, C. and
    Posner, I.},
    title = "{Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks}",
    Booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
    Month = {June},
    year = {2017},
    Pdf = {https://arxiv.org/abs/1609.06666}
    }

2016

  • [PDF] M. Wulfmeier, D. Rao, and I. Posner, “Incorporating Human Domain Knowledge into Large Scale Cost Function Learning,” in Neural Information Processing Systems Conference, Deep Reinforcement Learning Workshop, 2016.
    [Bibtex]

    @inproceedings{WulfmeierNIPS2016,
    author = {Wulfmeier, Markus and Rao, Dushyant and Posner, Ingmar},
    title = {Incorporating Human Domain Knowledge into Large Scale Cost Function Learning},
    journal = {CoRR},
    volume = {abs/1612.04318},
    Booktitle = {Neural Information Processing Systems Conference, Deep Reinforcement Learning Workshop},
    year = {2016},
    Pdf = {http://arxiv.org/abs/1612.04318},
    }

  • [PDF] J. Dequaire, D. Rao, P. Ondruska, D. Zeng Wang, and I. Posner, “Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks,” ArXiv e-prints, 2016.
    [Bibtex]

    @article{DequaireArXivSeptember2016,
    author = {Dequaire, J. and Rao, D. and Ondruska, P. and Zeng Wang, D. and Posner, I.},
    title = "{Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks}",
    journal = {ArXiv e-prints},
    archivePrefix = "arXiv",
    eprint = {1609.09365},
    primaryClass = "cs.CV",
    keywords = {Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Learning, Computer Science - Robotics},
    year = 2016,
    month = sep,
    Pdf = {https://arxiv.org/abs/1609.09365}
    }

Other Publications

2017

  • [PDF] D. Rao, M. De Deuge, N. Nourani–Vatani, S. B. Williams, and O. Pizarro, “Multimodal learning and inference from visual and remotely sensed data,” The International Journal of Robotics Research, vol. 36, pp. 24-43, 2017.
    [Bibtex]

    @article{rao2017ijrr,
    title={Multimodal learning and inference from visual and remotely sensed data},
    author={Rao, Dushyant and De Deuge, Mark and Nourani--Vatani, Navid and Williams, Stefan B and Pizarro, Oscar},
    journal={The International Journal of Robotics Research},
    volume={36},
    issue={1},
    pages={24 - 43},
    year={2017},
    pdf={http://journals.sagepub.com/doi/pdf/10.1177/0278364916679892}
    }

2016

  • [PDF] D. Rao, A. Bender, S. B. Williams, and O. Pizarro, “Multimodal information-theoretic measures for autonomous exploration,” in IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 4230-4237.
    [Bibtex]

    @inproceedings{rao2016multimodal,
    title={Multimodal information-theoretic measures for autonomous exploration},
    author={Rao, Dushyant and Bender, Asher and Williams, Stefan B and Pizarro, Oscar},
    booktitle={IEEE International Conference on Robotics and Automation (ICRA)},
    pages={4230--4237},
    year={2016},
    pdf={http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7487618}
    }

  • [PDF] D. Rao, “Multimodal learning from visual and remotely sensed data,” PhD Thesis, 2016.
    [Bibtex]

    @phdthesis{rao2015multimodal,
    title={Multimodal learning from visual and remotely sensed data},
    author={Rao, Dushyant},
    year={2016},
    school={University of Sydney},
    pdf={https://ses.library.usyd.edu.au/bitstream/2123/15535/2/rao_d_thesis.pdf}
    }

2015

  • [PDF] D. Rao, M. De Deuge, N. Nourani-Vatani, S. Williams, and O. Pizarro, “Multi-modality learning from visual and remotely sensed data,” in IROS Workshop on Alternative sensing for robot perception, 2015.
    [Bibtex]

    @inproceedings{rao2015multi,
    title={Multi-modality learning from visual and remotely sensed data},
    author={Rao, Dushyant and De Deuge, Mark and Nourani-Vatani, Navid and Williams, Stefan and Pizarro, Oscar},
    booktitle={IROS Workshop on Alternative sensing for robot perception},
    year={2015},
    pdf={http://www.rit.edu/kgcoe/iros15workshop/papers/IROS2015-WASRoP-Paper04.pdf}
    }

  • [PDF] M. Bewley, N. Nourani-Vatani, D. Rao, B. Douillard, O. Pizarro, and S. B. Williams, “Hierarchical classification in AUV imagery,” in Field and Service Robotics, 2015, pp. 3-16.
    [Bibtex]

    @inproceedings{bewley2015hierarchical,
    title={Hierarchical classification in {AUV} imagery},
    author={Bewley, MS and Nourani-Vatani, Navid and Rao, Dushyant and Douillard, Bertrand and Pizarro, Oscar and Williams, Stefan B},
    booktitle={Field and Service Robotics},
    pages={3--16},
    year={2015},
    pdf={https://www.researchgate.net/profile/Oscar_Pizarro2/publication/282824099_Hierarchical_Classification_in_AUV_Imagery/links/57d662cc08ae601b39aa7875.pdf}
    }

2014

  • [PDF] D. Rao, M. De Deuge, N. Nourani-Vatani, B. Douillard, S. B. Williams, and O. Pizarro, “Multimodal learning for autonomous underwater vehicles from visual and bathymetric data,” in IEEE International Conference on Robotics and Automation (ICRA), 2014, pp. 3819-3825.
    [Bibtex]

    @inproceedings{rao2014multimodal,
    title={Multimodal learning for autonomous underwater vehicles from visual and bathymetric data},
    author={Rao, Dushyant and De Deuge, Mark and Nourani-Vatani, Navid and Douillard, Bertrand and Williams, Stefan B and Pizarro, Oscar},
    booktitle={IEEE International Conference on Robotics and Automation (ICRA)},
    pages={3819--3825},
    year={2014},
    pdf={http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6907413}
    }

2012

  • [PDF] D. Rao, S. Chung, and S. Hutchinson, “CurveSLAM: An approach for vision-based navigation without point features,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012, pp. 4198-4204.
    [Bibtex]

    @inproceedings{rao2012curveslam,
    title={{CurveSLAM}: An approach for vision-based navigation without point features},
    author={Rao, Dushyant and Chung, Soon-Jo and Hutchinson, Seth},
    booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    pages={4198--4204},
    year={2012},
    pdf={http://arcl.ae.illinois.edu/IROS12_0762_FI.pdf}
    }

  • [PDF] D. Rao, “CurveSLAM: utilizing higher level structure in stereo vision-based navigation,” University of Illinois at Urbana-Champaign 2012.
    [Bibtex]

    @techreport{rao2012thesis,
    title={CurveSLAM: utilizing higher level structure in stereo vision-based navigation},
    author={Rao, Dushyant},
    year={2012},
    institution={University of Illinois at Urbana-Champaign},
    pdf={http://www-cvr.ai.uiuc.edu/~seth/ResPages/theses/Rao_DushyantMS.pdf}
    }

2011

  • [PDF] J. Yang, D. Rao, S. Chung, and S. Hutchinson, “Monocular vision based navigation in GPS-denied riverine environments,” in Infotech@ Aerospace Conference, , 2011, p. 1403.
    [Bibtex]

    @incollection{yang2011monocular,
    title={Monocular vision based navigation in {GPS}-denied riverine environments},
    author={Yang, Junho and Rao, Dushyant and Chung, Soon-Jo and Hutchinson, Seth},
    booktitle={Infotech@ Aerospace Conference},
    pages={1403},
    year={2011},
    pdf={http://authors.library.caltech.edu/72454/1/c8faa4ec88383c08587e4c4746dd21388b26.pdf}
    }

2009

  • [PDF] D. Rao and S. B. Williams, “Large-scale path planning for underwater gliders in ocean currents,” in Australasian Conference on Robotics and Automation (ACRA), 2009.
    [Bibtex]

    @inproceedings{rao2009large,
    title={Large-scale path planning for underwater gliders in ocean currents},
    author={Rao, Dushyant and Williams, Stefan B},
    booktitle={Australasian Conference on Robotics and Automation (ACRA)},
    year={2009},
    pdf={https://pdfs.semanticscholar.org/2d5c/2dae59cee6a2664148026c5d1b768fa7075c.pdf}
    }